1. Field of the Invention
The present invention relates to data communications systems and, more specifically, to a data communication system that communicates via a shared medium network.
2. Description of the Related Art
Shared medium networks, as used herein, are data communication networks in which several client devices communicate with an access point over a shared physical communication medium. A wireless local area network (often referred to as a “Wi-Fi network”) is an example on one type of shared medium network, in which several client devices transmit and receive data on a common wireless frequency channel. Generally, only a single device can transmit data at a time in such networks. Given that communicating devices on such networks often transmit and receive at irregular intervals, they require mechanisms to avoid contention between the devices.
Most Wi-Fi deployments today use the distributed coordination function (DCF) mode of the IEEE 802.11 standard to avoid contention between devices. The DCF mode of operation is simple and scalable, and requires a participating node to listen to the channel and make contention decisions purely on locally available information. The contention algorithm in turn is controlled by a set of parameters including the maximum contention window that are adaptively adjusted based on local information. While the approach is simple and scalable, the goal of DCF is to achieve coarse-level fairness and efficiency in the network. Any finer-level goals are usually considered to be beyond the scope of DCF.
The IEEE 802.11 point coordination function (PCF) mode, on the other hand, relies on centralized scheduling by the access-point (AP). Theoretically, the scheduling algorithm at the AP can be arbitrarily defined. The problems with PCF are two-fold, including: 1) it uses a polling process that incurs heavy overhead, especially in dynamic load conditions, and 2) the standard does not specify how APs should coordinate with each other to prevent collisions across cells.
There has been interest lately on the problem of achieving the benefits of centralized scheduling while retaining the simplicity and scalability benefits of distributed operations. The benefits of centralized scheduling are the following:                Predictability: Applications and services that require predictable service can expect to receive it in a setting with centralized scheduling. The central scheduler has complete control over what is transpiring in the network, and hence provides assurances.        Differentiation: Applications and services can be provided with different resource allocations depending on their requirements. While there are distributed approaches to accomplish this goal (e.g., IEEE 802.11e), they may be quite coarse in the differentiation they provide.        Efficiency: In environments where operational efficiency is an issue (e.g., in high-density Wi-Fi deployments), centralized scheduling can lead to higher efficiencies.        
On the other hand, the advantages of purely distributed operations are the lack of a single point of failure or bottleneck, scalability with the number of nodes, and backward compatibility with how Wi-Fi is predominantly used today.
While the DCF standard offers efficiency, it offers a low level of control. This can be important when different processes have different priorities. For example, a device streaming a movie on a wireless device would need a higher level of continuity in data transmission than a device engaged in a periodic operating system update. However, with a typical DCF communication system, both devices would communicate with the same priority—which could result in a lower quality of service for the device streaming the movie.
PCF offers a higher level of control. However, it is less efficient because it spends time polling the devices to see if they have data to transmit.
Therefore, there is a need for a data communication system that is both efficient and that allows a high level of control among the transmitting devices.